Diffusion MRI in Cervical Spondylotic Myelopathy

Cervical Spondylotic Myelopathy

diffusion MRI in evaluates and predicts prognosis in CSM

Cervical spondylotic myelopathy (CSM) is a spinal dysfunction disease common in the elderly population caused by cervical spine degeneration, spinal canal stenosis, and spinal cord compression. It may result in reduced quality of life or even disability. With the increased life expectancy of today's population, the incidence of CSM is increasing. Surgery is recommended to reduce compression of the spinal cord. However, due to individual differences and variations in spinal cord injury severity, the prognosis after surgery is often unpredictable. Therefore, proper evaluation of spinal cord function and prognosis prediction are important considerations for the clinical decision of whether to operate and selection of appropriate operation time. To achieve this goal, medical images are used to correctly evaluate the damage and recovery potential of neurons. Magnetic resonance imaging (MRI) provides spinal cord macrostructure details and can detect spinal cord damage. Clinically, conventional MRI is often used to confirm a CSM diagnosis and predict prognosis. However, MRI assessments, including increased signal intensity (ISI) and T1 hypo-intensity, might not be consistent with clinical manifestations or prognostic expectations. Diffusion MRI (dMRI) enables early diagnoses and prognostic predictions due to its microstructure assessment advantages. The diffusion of water molecules is restricted due to structural barriers, such as axon membranes and myelin sheaths. Using the microscopic movement of water molecules, dMRI can detect microstructures indirectly using a model with specific underlying probability distribution function of diffusion. Three models are widely applied clinically: diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI). DTI assumes the diffusion distribution function to be Gaussian, DKI assumes it to be non-Gaussian, and NODDI assumes it to be multi-compartmental (intracellular pool, extracellular pool, and free water). Previous studies suggested the potential application value of DTI and DKI in patients with CSM; however, these models had limited specificity and were not sufficient to diagnose CSM in a clinical setting. Compared with DTI and DKI, NODDI has been shown to characterize spinal cord microstructure better.

No related papers found yet.

China